ebdm/session7.Rmd at main · matarui/ebdm · GitHub

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---
title: "Counterfactuals"
description: |
  What alternatives do we have to experiments?
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = FALSE)
```

![Searching for counterfactuals... <br> <span>photo by <a href="https://unsplash.com/@supernov?utm_source=unsplash&amp;utm_medium=referral&amp;utm_content=creditCopyText">Edi Libedinsky</a> on <a href="https://unsplash.com/s/photos/binoculars?utm_source=unsplash&amp;utm_medium=referral&amp;utm_content=creditCopyText">Unsplash</a></span>](photos/edi-libedinsky-1bhp9zBPHVE-unsplash.jpg)

## Background Video

### Counterfactuals, counterfactuals, counterfactuals everywhere

There are many ways to make inferences but most (all?!?) forms of causal inference involve some form of counterfactual. Take some time to think about the concept of counterfactuals by watching this short intro (5 minutes).

<iframe width="560" height="515" src="https://www.youtube.com/embed/5eNhS0oaLHo" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen></iframe>

## Required Reading

Read **Varian (2016)** and **Grosz et al. (2024)* (ca. 120 minutes) to get an overview of causal inference strategies.

Varian, H. R. (2016). Causal inference in economics and marketing. *Proceedings of the National Academy of Sciences of the United States of America, 113*(27), 7310–7315. [http://doi.org/10.1073/pnas.1510479113](https://github.com/matarui/ebdm/raw/main/docs/literature/Varian_2016_PNAS.pdf)

Grosz, M. P., Ayaita, A., Arslan, R. C., Buecker, S., Ebert, T., Hünermund, P., Müller, S. R., Rieger, S., Zapko-Willmes, A., & Rohrer, J. M. (2024). Natural experiments: missed opportunities for causal inference in psychology. *Advances in Methods and Practices in Psychological Science, 7(1)*,1-15. [https://journals.sagepub.com/doi/10.1177/25152459231218610](https://journals.sagepub.com/doi/10.1177/25152459231218610)

## Session Slides

![Alternatives to experiments](presentations/EBDM_session7.pdf){width=700px height=500px}

<!-- ## Additional Resources -->

<!-- ### Further Reading -->

<!-- Here's a popular science book on the "new" science of causal inference:  -->

<!-- Pearl, J. & Mackenzie, D. (2018). *The book of why: The new science of cause and effect.* Basic Books. [https://www.basicbooks.com/titles/judea-pearl/the-book-of-why/9781541698963/](https://www.basicbooks.com/titles/judea-pearl/the-book-of-why/9781541698963/) -->